Polyether polyols as GPC calibration standards for determination of molecular weight distribution of polyether polyols

ABSTRACT Average molecular weights (Mn, Mw and Mp) are important characteristics of oligomers and polymers, and therefore there is a need to have a precise and reliable determination method. A gel permeation chromatography (GPC) coupled with a single refractive index detector was used to determine t...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of applied polymer science 2015-11, Vol.132 (43), p.np-n/a
Hauptverfasser: Mohd Noor, Mohd Azmil, Sendijarevic, Vahid, Abu Hassan, Hazimah, Sendijarevic, Ibrahim, Tuan Ismail, Tuan Noor Maznee, Seng Soi, Hoong, Hanzah, Nurul 'Ain, Ghazali, Razmah
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:ABSTRACT Average molecular weights (Mn, Mw and Mp) are important characteristics of oligomers and polymers, and therefore there is a need to have a precise and reliable determination method. A gel permeation chromatography (GPC) coupled with a single refractive index detector was used to determine the molecular weight distributions of commercial polyether polyols calibrated against a series of polyether polyols with known molecular weights and low polydispersity. Results of these GPC analyses were compared to the ones calibrated against the commercially available polystyrene (PS) standards. The number‐average molecular weights (Mn) obtained with GPC using polyether polyols calibration were closer to the theoretical values than the Mn obtained using PS as calibration standards. Hence, these GPC analyses using polyether polyols as calibration standards can provide reliable determination of molecular weight distribution of polyether polyols and can be potentially applied to natural oil‐based polyols, including palm oil‐based polyols. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015, 132, 42698.
ISSN:0021-8995
1097-4628
DOI:10.1002/app.42698